Monolithic AI vs Modular AI

[@CharlotteLopez-n3i]

Love the emphasis on modularity and specification in building reliable AI systems! The organic solar cells example is a great illustration of how a model-based approach can lead to more efficient solutions.

[@davidtindell950]

thank you for your ENTHUSIASM ! ! ! !😊

[@code4AI]

Always!

[@aennmatyasbarra-hunyor5506]

Great series

[@code4AI]

Thank you.

[@pensiveintrovert4318]

So their genius idea is that a specialist is better at its specialty than a generalist? I can expect this kind of insight from a chatGPT when I ask it to explain something to a five year old. That is why mixture of experts works better than a monolith model.

[@code4AI]

No. The idea is, that you have to design your AI architecture and the different NN configurations in your layers in a specific way, and that your specific task is the main design criterium for a dedicated and optimized AI architecture.

[@ibgib]

This is highly close to what I've been building: semantic version control. It's like a generalized git. Specification is one layer on top of version control. The protocol enables content addressing (like git commit hashes) to version specs, models, training data, metadata like agentic architectures, and even derivative data. This very instant, I'm working on agent-based JIT UX. Still looking for investment!